#include "main.h"

#include <Eigen/CXX11/Tensor>

using Eigen::RowMajor;
using Eigen::Tensor;

static void
test_comparison_sugar()
{
	// we already trust comparisons between tensors, we're simply checking that
	// the sugared versions are doing the same thing
	Tensor<int, 3> t(6, 7, 5);

	t.setRandom();
	// make sure we have at least one value == 0
	t(0, 0, 0) = 0;

	Tensor<bool, 0> b;

#define TEST_TENSOR_EQUAL(e1, e2)                                                                                      \
	b = ((e1) == (e2)).all();                                                                                          \
	VERIFY(b())

#define TEST_OP(op) TEST_TENSOR_EQUAL(t op 0, t op t.constant(0))

	TEST_OP(==);
	TEST_OP(!=);
	TEST_OP(<=);
	TEST_OP(>=);
	TEST_OP(<);
	TEST_OP(>);
#undef TEST_OP
#undef TEST_TENSOR_EQUAL
}

static void
test_scalar_sugar_add_mul()
{
	Tensor<float, 3> A(6, 7, 5);
	Tensor<float, 3> B(6, 7, 5);
	A.setRandom();
	B.setRandom();

	const float alpha = 0.43f;
	const float beta = 0.21f;
	const float gamma = 0.14f;

	Tensor<float, 3> R = A.constant(gamma) + A * A.constant(alpha) + B * B.constant(beta);
	Tensor<float, 3> S = A * alpha + B * beta + gamma;
	Tensor<float, 3> T = gamma + alpha * A + beta * B;

	for (int i = 0; i < 6 * 7 * 5; ++i) {
		VERIFY_IS_APPROX(R(i), S(i));
		VERIFY_IS_APPROX(R(i), T(i));
	}
}

static void
test_scalar_sugar_sub_div()
{
	Tensor<float, 3> A(6, 7, 5);
	Tensor<float, 3> B(6, 7, 5);
	A.setRandom();
	B.setRandom();

	const float alpha = 0.43f;
	const float beta = 0.21f;
	const float gamma = 0.14f;
	const float delta = 0.32f;

	Tensor<float, 3> R = A.constant(gamma) - A / A.constant(alpha) - B.constant(beta) / B - A.constant(delta);
	Tensor<float, 3> S = gamma - A / alpha - beta / B - delta;

	for (int i = 0; i < 6 * 7 * 5; ++i) {
		VERIFY_IS_APPROX(R(i), S(i));
	}
}

EIGEN_DECLARE_TEST(cxx11_tensor_sugar)
{
	CALL_SUBTEST(test_comparison_sugar());
	CALL_SUBTEST(test_scalar_sugar_add_mul());
	CALL_SUBTEST(test_scalar_sugar_sub_div());
}
